Covid-19 Prediction in Indonesia Capital Buffer with K Nearest Neighbor Regression

被引:0
作者
Overbeek, Marlinda Vasty [1 ]
Stephanno, Aldo Gabriel Yoseph [1 ]
Surbakti, Eunike Endariahna [1 ]
Tobing, Fenina Adline Twince [1 ]
机构
[1] Univ Multimedia Nusantara, Dept Informat, Tangerang, Indonesia
来源
2021 5TH INTERNATIONAL CONFERENCE ON INFORMATICS AND COMPUTATIONAL SCIENCES (ICICOS 2021) | 2021年
关键词
Covid-19; prediction; K-Nearest Neighbor Regression; Indonesia Capital Buffer; Tangerang Regency; Regression Analysis;
D O I
10.1109/ICICOS53627.2021.9651749
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Covid-19 is an infectious disease caused by the SARS-CoV-2 virus. This virus first appeared in the city of Wuhan, China in December 2019. Since the appearance of this first case, around 25 countries have confirmed the emergence of similar cases in their countries. On March 2, 2020, the Indonesian government announced the emergence of the first Covid-19 case. Since then, the growth of the Covid-19 case in Indonesia has continued to increase day by day and has spread to all provinces in Indonesia. Tangerang regency, as one of Indonesia's Capital Buffer, has an important role in supporting the needs of the capital. This study will discuss how to predict the number of Covid-19 cases in Tangerang regency using the K-Nearest Neighbors Regression method because the increase in positive cases in the capital Jakarta and Tangerang could occur due to the mobility between two regions. This method was chosen because its performance is considered good and can analyze the predicted value based on the relationship between the existing variables, although it requires large enough data. The prediction model made has been evaluated using several error rate calculations and produces the best accuracy value of 96.98% and the worse accuracy value given 79.97%.
引用
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页数:6
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